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VMs Placement Strategy based on Distributed Parallel Ant Colony Optimization Algorithm |
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PP: 873-881 |
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Author(s) |
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Gaochao Xu,
Yushuang Dong,
Xiaodong Fu,
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Abstract |
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| Cloud computing is at the forefront of information technology. Cloud computing led to abandon the use of expensive
mainframe. It becomes a trend that data center uses the cluster which is relatively cheap and virtualization technologies to provide
infrastructure services. To improve the utilization rate of the cloud center and decrease the operating cost, the cloud center provides
services to users as required by sharding the resources with virtualization. Because consideration should be given to both QoS for
users and cost saving for cloud computing providers, cloud providers try to maximize performance and minimize energy cost as well.
In this paper, we propose a Distributed Parallel Ant Colony Optimization (DPACO) Algorithm of placement strategy for live virtual
machines Live Migration on cloud platform. It executes the ant colony optimization algorithm parallelly and distributedly on several
selected physical hosts in the first stage. Then it continues to execute the second stage ant colony optimization algorithm with solutions
calculated by the first stage. The solution calculated by the second stage ant colony optimization algorithm is the optimal solution of
our approach. The experimental results have shown that the proposed placement strategy of VM live migration is more effective and
energy-efficient with ensuring QoS for users than other placement strategies on the cloud platform. |
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